User profiling based on transaction data associated with a user

Abstract

A user profile scoring platform may analyze a transaction log of a transaction account of a user to determine, based on transactions of the transaction log, a qualification status of the user, wherein the qualification status indicates that a characteristic of the user satisfies a threshold qualification metric. The user profile scoring platform may determine, based on the qualification status, a transaction-based score associated with the user, wherein the transaction-based score is determined using a transaction log analysis model. The user profile scoring platform may obtain, based on receiving the access information, a user score associated with a user transaction history that is associated with a plurality of transaction accounts that are associated with the user and different from the transaction account. The user profile scoring platform may perform an action based on the transaction-based score and the user score.

What is claimed is: 
     
       1. A method, comprising:
 analyzing, by a device and based on receiving access information, a first transaction log of a transaction account of a user; 
 determining, by the device and based on transactions of the first transaction log, a qualification status of the user,
 wherein the qualification status indicates that a characteristic of the user satisfies a threshold qualification metric; 
 
 determining, by the device and based on the qualification status, a transaction-based score associated with the user,
 wherein the transaction-based score is determined using a transaction log analysis model comprising a machine learning model that is trained based on:
 historical data associated with previous transactions of other second transaction logs, and 
 previous scores associated with users of the other second transaction logs; 
 
 
 providing, by the device, a link to a user device associated with the user,
 wherein the link enables a communication session between the user device and an external user-scoring platform, and 
 wherein a message is transmitted to a messaging account associated with the user based on the communication session being established based on the link; 
 
 processing, by the device and based on accessing the messaging account, a plurality of messages, including the message, in the messaging account; 
 obtaining, by the device and based on processing the plurality of messages, a user score associated with a user transaction history that is associated with a plurality of transaction accounts that are associated with the user and different from the transaction account; 
 determining, by the device, a difference between the transaction-based score and the user score; 
 retraining, by the device, and based on the difference and the first transaction log, the machine learning model; and 
 performing, by the device, an action based on the transaction-based score and the user score. 
 
     
     
       2. The method of  claim 1 , further comprising, prior to analyzing the first transaction log:
 receiving a user input that authorizes an analysis of the transaction account,
 wherein the user input includes the access information; and 
 
 performing a verification process to verify that the user provided the user input,
 wherein the first transaction log is analyzed based on results of performing the verification process. 
 
 
     
     
       3. The method of  claim 1 , wherein determining the qualification status of the user comprises:
 receiving a user input associated with the characteristic,
 wherein the user input indicates that the transaction account qualifies as a prioritized transaction account; and 
 
 determining the qualification status of the user based on the user input. 
 
     
     
       4. The method of  claim 1 , wherein the first transaction log analysis model is configured to determine the transaction-based score based on at least one of:
 a percentage of transactions identified in the first transaction log that are associated with a transaction type, or 
 a time period associated with the transactions. 
 
     
     
       5. The method of  claim 1 , wherein obtaining the user score comprises:
 processing a message of a message account to determine the user score. 
 
     
     
       6. The method of  claim 1 , wherein the action is a first action, the method further comprising:
 determining, based on the difference, a condition associated with the user; and 
 performing, based on the condition, a second action associated with the user. 
 
     
     
       7. The method of  claim 6 , wherein performing the second action comprises at least one of:
 providing, to a user device of the user, a report that addresses the difference, 
 providing, to the user, an offer for a product that is configured to reduce the difference, or 
 designating the user as pre-authorized for a future transaction involving the product. 
 
     
     
       8. The method of  claim 1 , wherein processing the plurality of messages comprises:
 identifying terms in at least one of:
 body of a particular message of the plurality of messages, 
 subject line of the particular message, or 
 sender information of the particular message. 
 
 
     
     
       9. A device, comprising:
 one or more memories; and 
 one or more processors, coupled to the one or more memories, configured to:
 analyze, based on receiving access information, a first transaction log of a transaction account of a user; 
 determine, based on transactions of the first transaction log, a qualification status of the user,
 wherein the qualification status indicates that a characteristic of the user satisfies a threshold qualification metric; 
 
 determine, based on the qualification status, a transaction-based score associated with the user,
 wherein the transaction-based score is determined using a transaction log analysis model comprising a machine learning model that is trained based on:
 historical data associated with previous transactions of other second transaction logs, and 
 previous scores associated with users of the other second transaction logs; 
 
 
 provide a link to a user device associated with the user,
 wherein the link enables a communication session between the user device and an external user-scoring platform, and 
 wherein a message is transmitted to a messaging account associated with the user based on the communication session being established based on the link; 
 
 process, based on accessing the messaging account, a plurality of messages, including the message, in the messaging account; 
 obtain, based on processing the plurality of messages, a user score associated with a user transaction history that is associated with a plurality of transaction accounts that are associated with the user and different from the transaction account; 
 determine a difference between the transaction-based score and the user score; 
 retrain, by the device, and based on the difference and the first transaction log, the machine learning model; and 
 perform an action based on the transaction-based score and the user score. 
 
 
     
     
       10. The device of  claim 9 , wherein the one or more processors, prior to analyzing the first transaction log, are further configured to:
 receive a user input that authorizes an analysis of the transaction account,
 wherein the user input includes the access information; and 
 
 perform a verification process to verify that the user provided the user input,
 wherein the first transaction log is analyzed based on results of performing the verification process. 
 
 
     
     
       11. The device of  claim 9 , wherein the one or more processors, to determine the qualification status of the user, are configured to:
 receive a user input associated with the characteristic,
 wherein the user input indicates that the transaction account qualifies as a prioritized transaction account; and 
 
 determine the qualification status of the user based on the user input. 
 
     
     
       12. The device of  claim 9 , wherein the transaction log analysis model is configured to determine the transaction-based score based on at least one of:
 a percentage of transactions identified in the first transaction log that are associated with a transaction type, or 
 a time period associated with the transactions. 
 
     
     
       13. The device of  claim 9 , wherein the one or more processors, to obtain the user score, are configured to:
 process a message of a message account to determine the user score. 
 
     
     
       14. The device of  claim 9 , wherein the action is a first action, and wherein the one or more processors are configured to:
 determine, based on the difference, a condition associated with the user; and 
 perform, based on the condition, a second action associated with the user. 
 
     
     
       15. A non-transitory computer-readable medium storing a set of instructions, the set of instructions comprising:
 one or more instructions that, when executed by one or more processors of a device, cause the device to:
 analyze, based on receiving access information, a first transaction log of a transaction account of a user; 
 determine, based on transactions of the first transaction log, a qualification status of the user,
 wherein the qualification status indicates that a characteristic of the user satisfies a threshold qualification metric; 
 
 determine, based on the qualification status, a transaction-based score associated with the user,
 wherein the transaction-based score is determined using a transaction log analysis model comprising a machine learning model that is trained based on:
 historical data associated with previous transactions of other second transaction logs, and 
 previous scores associated with users of the other second transaction logs; 
 
 
 provide a link to a user device associated with the user,
 wherein the link enables a communication session between the user device and an external user-scoring platform, and 
 wherein a message is transmitted to a messaging account associated with the user based on the communication session being established based on the link; 
 
 process, based on accessing the messaging account, a plurality of messages, including the message, in the messaging account; 
 obtain, based on processing the plurality of messages, a user score associated with a user transaction history that is associated with a plurality of transaction accounts that are associated with the user and different from the transaction account; 
 determine a difference between the transaction-based score and the user score; 
 retrain, by the device, and based on the difference and the first transaction log, the machine learning model; and 
 perform an action based on the transaction-based score and the user score. 
 
 
     
     
       16. The non-transitory computer-readable medium of  claim 15 , wherein the one or more instructions, prior to analyzing the first transaction log, further cause the device to:
 receive a user input that authorizes an analysis of the transaction account,
 wherein the user input includes the access information; and 
 
 perform a verification process to verify that the user provided the user input,
 wherein the first transaction log is analyzed based on results of performing the verification process. 
 
 
     
     
       17. The non-transitory computer-readable medium of  claim 15 , wherein the one or more instructions, that cause the device to determine the qualification status of the user, cause the device to:
 receive a user input associated with the characteristic,
 wherein the user input indicates that the transaction account qualifies as a prioritized transaction account; and 
 
 determine the qualification status of the user based on the user input. 
 
     
     
       18. The non-transitory computer-readable medium of  claim 15 , wherein the one or more instructions further cause the device to determine the transaction-based score based on at least one of:
 a percentage of transactions identified in the first transaction log that are associated with a transaction type, or 
 a time period associated with the transactions. 
 
     
     
       19. The non-transitory computer-readable medium of  claim 15 , wherein the one or more instructions, that cause the device to obtain the user score, cause the device to:
 process a message of a message account to determine the user score. 
 
     
     
       20. The non-transitory computer-readable medium of  claim 15 , wherein the one or more instructions further cause the device to:
 determine, based on the difference, a condition associated with the user; and 
 perform, based on the condition, a second action associated with the user.